4 th AEGC: Geoscience – Breaking New Ground – 13-18 March 2023, Brisbane, Australia 1 Evolution of depth estimation techniques by using potential field data Desmond FitzGerald Jeffrey B. Thurston Ed. K. Biegert Intrepid Geophysics Intrepid Geophysics Rice University des@intrepid-geophysics.com jeff.thurston@intrepid-geophysics.com biegert@alumni.rice.edu SUMMARY Depth estimation methods should be selected according to the data quality and the nature of one's particular geologic problem. Magnetic depth estimation is a cost-effective and useful tool of quantitative interpretation and helps reduce exploration risk. To produce a reliable depth solution, the experience of an interpreter is important and other independent controls are necessary. This follows from an understanding of what the indicated depths might represent. Also, as a gradient calculation is usually involved, noise creates a spread of depth solutions. The new Cauchy derivatives by integration are stabilized and more precise. This stems from exploiting potential field holomorphic properties, which have largely been ignored in exploration geophysics. This leads to enhanced noise suppression and a more stable version of the `signal` in complex number form. Falcon airborne gravity gradiometer surveys may benefit from some of this work as well. Padé Approximation in conjunction with Cauchy methods leads to a coherent downward continuation of the magnetic field. Depth to basement, is now nuanced to include depth to weathering, depth to top/bottom of discreate magnetic sources. Key words: potential field depths, vertical gradients, tensor gradients, random dipoles. INTRODUCTION A complete quantitative interpretation of potential field data aims to estimate three types of information about sources of geological interest: depth, dimensions, and the distribution of relevant physical properties. In many applications depth estimates are of great interest. The confusing aspect is “depth to what?”. Historically, different methods have been developed to estimate depths to magnetic sources including Euler/Werner deconvolution, Naudy, Source Parameter Imaging- improved (iSPI), and spectral analysis. All these methods have benefits and issues. All methods rely on calculated derivatives of the measured magnetic field. As Moore’s law has delivered effectively unlimited computing capacity, today more correct methods can be implemented. In attempting to explain the typical results obtained, the habit of calling the results the “magnetic basement”, as opposed to the “seismic basement”, or “density contrast” basement has crept into the lexicon. This is an approximation at best. None of this mathematics is new, being more than 100 years old. Existing approaches cut corners which leads to numerical instability and compromised results. The Cauchy method provides high fidelity gradient estimation and detection and reduced ambiguity. In this paper, the performance of the Padé Approximation in conjunction with Cauchy methods is demonstrated using a range of synthetic models and “borehole calibrated” real-life examples. The popular Tikhonov inversion pipeline also comes under scrutiny. These data sets have been used to check the older methods named above, providing a comparison of methods. To investigate the robustness of the method, noise is added to the synthetic dataset and the results are considered with the other methods. DIFFERENT METHODS FOR ESTIMATING MAGNETIC DEPTHS to 2005 (Li, 2003) laid out a clear summary of historic popular magnetic depth estimation algorithms. This is neither magnetic inversion nor a “black box.” Most importantly, an accurate inversion requires many constraints. Depth estimation methods work for simplified source geometries and are independent of the susceptibility contrast. The automatic methods are also independent of magnetization direction. These depth estimate methods can be briefly assessed as follows: